Skip to main content
Sandbox Physics

2026 FIELDS MEDAL · YU DENG

One box.Three worlds.

Every sphere obeys Newton’s laws. Why should the gas as a whole obey a different, statistical equation? Writing down both descriptions is easy. Proving that they remain one story after a long history of collisions is not.

Citation threads
PDE · probability · mathematical physics
Reading time
About 12 minutes
Sources
8 items · source-graded
01

Microscopic

Track particlesPosition, velocity, elastic impact
02

Mesoscopic

Track a distributionProbability density over position and velocity
03

Macroscopic

Track a fluidDensity, temperature, bulk velocity
The particles are not replaced by an equation. In a dilute limit, two descriptions are proved to make the same statistical predictions.

01 / STATE THE PROBLEM

The achievement is not a new equation. It is a proof that two worlds really connect.

Imagine a transparent box. Inside it there is no “temperature,” no “pressure,” and no gas treated as one object. There are only hard spheres: straight flights interrupted by elastic collisions. If every position and velocity were known, Newtonian mechanics would determine the next moment.

That is not how we normally describe air. We use temperature and pressure, or a functionf(t,x,v)f(t,x,v)that counts how much matter lies near position xx with velocityvv at time tt. This is the language of the Boltzmann equation.

The difficult word is “proved.” Physics had long relied on the bridge, and computation had long used the equation on the far side. The mathematical obstacle was to show why the statistical description remains valid after collisions create long, shared histories among particles.

02 / THREE LANGUAGES FOR ONE GAS

Pull the camera back, and the main character changes

At the microscopic scale, every sphere moves freely between impacts, with momentum and kinetic energy redistributed at each elastic collision. The description is concrete but enormous.

MICROSCOPIC
x˙i=vi,v˙i=0\dot x_i=v_i,\qquad \dot v_i=0

Track each particle between impacts.

KINETIC
tf+vxf=Q(f,f)\partial_t f+v\cdot\nabla_x f=Q(f,f)

Ask how many particles belong to each class.

FLUID
ρ(t,x),u(t,x),T(t,x)\rho(t,x),\quad u(t,x),\quad T(t,x)

Density, bulk velocity, and temperature take over.

At the kinetic scale, particle identity disappears. Free transport sits on the left of the Boltzmann equation; the collision operatorQ(f,f)Q(f,f)records how impacts move particles among velocity classes.

At the macroscopic scale, moments of the distribution produce fluid variables. A companion work by Deng, Hani, and Ma continues the chain to compressible Euler and incompressible Navier–Stokes–Fourier equations within the dilute hard-sphere framework and limiting regimes stated in the paper.[3]

03 / THE TWO WORDS THAT BLOCKED THE ROAD

For a short time, particles are strangers. Later, they share a past.

Oscar Lanford established the hard-sphere-to-Boltzmann bridge in 1975, but only for a sufficiently short interval. The new work extends the derivation to arbitrarily long intervals, provided the corresponding Boltzmann solution continues to exist.[2][7]

Waiting longer changes the proof because a collision creates both a new velocity and a relationship. A hits B, B later hits C, and C eventually meets A again. Treating A and C as independent samples can now double-count or miss correlations.

t₀t₁t₂t₃

The number of impacts is not the only difficulty. The same particles can meet again through different paths.

Microscopic hard-sphere dynamics is reversible, while the Boltzmann equation carries a statistical direction of time. The theorem is not a one-line solution to the arrow of time. It proves, under precise low-density and initial-data hypotheses, that an effective statistical evolution can emerge from reversible dynamics and remain valid over long times.

04 / THE TECHNICAL DRAMA

Keep the memory: encode collision histories as “molecules,” then cut carefully

One turning point began with a simple question: if a long interval is too difficult, can it be divided into short ones? Deng has recalled that the idea arrived in a Korean fried-chicken shop in Providence.[8]The answer required a new framework because every time layer creates more possible collision histories.

  1. 01

    Layer time

    Break a long interval into short windows while preserving the information passed between them.

  2. 02

    Record correlations with cumulants

    Do not pretend particles remain independent; track the strength of their shared histories.

  3. 03

    Encode histories as CH molecules

    Translate complicated integrals into combinatorial diagrams whose loops and layers reveal dangerous histories.

  4. 04

    Cut and control the remainder

    Use a careful algorithm to decompose large structures into pieces that can be bounded.

The original paper describes the core in the same order: propagate a long-time cumulant structure that retains full collision history, reduce the estimates to combinatorial properties of collision-history diagrams, and control them with an elaborate cutting algorithm.[2]“Cutting” here means a legitimate decomposition of the estimate, not discarding inconvenient cases.

05 / THE KNIFE WAS FIRST SHARPENED ON WAVES

Particles collide and waves resonate, but the mathematical obstruction has a familiar shape

Before hard spheres, Deng and Hani studied wave turbulence. The microscopic side is a nonlinear Schrödinger equation tracking phases and interactions. The statistical side is a wave kinetic equation tracking average energy transfer among Fourier modes.

PARTICLESHard-sphere impacts

Identifiable particles generate an expanding collision genealogy.

NewtonBoltzmann\text{Newton}\Longrightarrow\text{Boltzmann}
WAVESMode resonances

Deterministic waves generate increasingly complicated interaction trees.

NLSWKE\text{NLS}\Longrightarrow\text{WKE}

They first derived the wave kinetic equation at the kinetic timescale under a specified scaling law, then addressed a fuller range of scalings. The later work identifies arbitrarily large bad diagrams, uncovers systematic cancellations among them, and builds a robust algorithm for the remaining diagrams.[4][5]

Particles and waves are physically different. What they share is the demand to derive a statistical equation from deterministic microscopic dynamics. The long-time expansions and diagrammatic experience developed for waves became a template for the hard-sphere problem.

06 / RANDOMNESS IS STRUCTURE, NOT NOISE

One wave can become unrecognizable while the ensemble law stays the same

The official medal citation also highlights Deng’s probabilistic approaches to nonlinear Schrödinger dynamics. Randomness here is not an arbitrary perturbation. Initial data is sampled from a precisely defined statistical ensemble.[1]

With Andrea Nahmod and Haitian Yue, Deng studied defocusing nonlinear Schrödinger equations on the two-dimensional torus. They proved almost-sure global well-posedness with respect to the associated Gibbs measure and obtained invariance of that measure under the dynamics, using new random averaging operators.[6]

The common theme with kinetic theory is striking: individual trajectories may be extremely complicated, but if probabilistic structure propagates, collective laws can remain stable, rigorous, and predictive.

07 / PRECISION MAKES THE RESULT STRONGER

What the work establishes — and what it does not claim

  • It establishes a long-time bridge. In the paper’s dilute hard-sphere limit and regularity regime, the Boltzmann description remains valid throughout the lifespan of the corresponding solution.

  • It reaches a central program within Hilbert’s sixth problem. The companion paper connects Newtonian particles through Boltzmann kinetics to fluid equations in this setting.

  • It is not a statement about every material, initial condition, or time. Hard spheres, the dilute limit, initial statistical structure, and the lifespan of the Boltzmann solution are part of the theorem.

  • It does not axiomatize all of physics at once. The accurate claim concerns the Newton-to-fluid program through Boltzmann kinetic theory for a specific dilute hard-sphere gas.

08 / NOW MAKE IT MOVE

Animation will not “prove” the theorem. It will make the proof’s hardest objects visible.

The first interactive release combines the first two questions on one synchronized stage, following this article’s chain of evidence:

LAB 01 · LIVE

Two views of one gas

Track hard spheres on the left and only their empirical distribution on the right. Change particle count and dilution to compare the descriptions.

LAB 02 · LIVE

Draw collision genealogies

Select a particle and unfold its collision history. Watch an ordinary branch become a correlation loop after a recollision.

LAB 03 · NEXT

Cut long time by hand

Compare a single expansion with a layered one, seeing why short windows simplify local behavior while creating combinatorial bookkeeping.

INTERACTIVE LAB · LIVEEnter “Hard Spheres to Boltzmann”

Understand what the picture means before making it move. Then a simulation becomes a microscope for the argument, not fireworks after the conclusion.

SOURCES / CITATION POLICY

Where each claim comes from

The article prioritizes the IMU’s official citation and original research papers. News sources support only biographical or process details, and preprints are labeled rather than presented as published papers.

  1. [1]

    Official citation

    Fields Medal 2026 — Yu Deng: Short and Long Citation

    International Mathematical Union

    International Congress of Mathematicians 2026

    Primary authority for the scope of the medal citation.
    Open source
  2. [2]

    Original research · preprint

    Long time derivation of the Boltzmann equation from hard sphere dynamics

    Yu Deng, Zaher Hani, Xiao Ma

    arXiv:2408.07818; Annals of Mathematics, to appear

    The central long-time derivation from hard-sphere dynamics.
    Open source
  3. [3]

    Original research · preprint

    Hilbert’s sixth problem: derivation of fluid equations via Boltzmann’s kinetic theory

    Yu Deng, Zaher Hani, Xiao Ma

    arXiv:2503.01800

    Continues the bridge from Boltzmann to fluid equations in the dilute hard-sphere setting.
    Open source
  4. [4]

    Original research · published

    Full derivation of the wave kinetic equation

    Yu Deng, Zaher Hani

    Inventiones Mathematicae 233, 543–724

    A rigorous derivation of wave kinetics from nonlinear Schrödinger dynamics.
    Open source
  5. [5]

    Original research · preprint

    Derivation of the wave kinetic equation: full range of scaling laws

    Yu Deng, Zaher Hani

    arXiv:2301.07063

    Source for bad diagrams, systematic cancellation, and the bounding algorithm.
    Open source
  6. [6]

    Original research · published

    Invariant Gibbs measures and global strong solutions for nonlinear Schrödinger equations in dimension two

    Yu Deng, Andrea R. Nahmod, Haitian Yue

    Annals of Mathematics 200(2), 399–486

    Primary source for Gibbs invariance and random averaging operators.
    Open source
  7. [7]

    Proof guide · preprint

    Derivation of the Boltzmann equation from hard-sphere dynamics (after Y. Deng, Z. Hani, and X. Ma)

    Thierry Bodineau, Isabelle Gallagher, Laure Saint-Raymond, Sergio Simonella

    arXiv:2602.04407

    An expert exposition of the proof architecture.
    Open source
  8. [8]

    Institutional reporting

    UChicago Prof. Yu Deng receives Fields Medal, highest honor in mathematics

    University of Chicago News

    University of Chicago

    Background for the research process and the short-time-interval insight.
    Open source